Identifying the evolution of disasters and responses with network-text analysis. - Kyungwoo Song; Do-Hyeong Kim; Su-Jin Shin; Il-Chul Moon (SMC, 2014)

The Regularity of Semihyperbolic Patches Near Sonic Lines for The 2-D Euler System in Gas Dynamics. - Kyungwoo Song; Qin Wang; Yuxi Zheng (SIAM J. Math. Anal., 2015)

Data-driven ballistic coefficient learning for future state prediction of high-speed vehicles. - Kyungwoo Song; Sang-Hyeon Kim; Jinhyung Tak; Han-Lim Choi; Il-Chul Moon (FUSION, 2016)

Augmented Variational Autoencoders for Collaborative Filtering with Auxiliary Information. - Wonsung Lee; Kyungwoo Song; Il-Chul Moon (CIKM, 2017)

Neural Ideal Point Estimation Network. - Kyungwoo Song; Wonsung Lee; Il-Chul Moon (AAAI, 2018)

Adversarial Dropout for Recurrent Neural Networks. - Sungrae Park; Kyungwoo Song; Mingi Ji; Wonsung Lee; Il-Chul Moon (AAAI, 2019)

Hierarchical Context Enabled Recurrent Neural Network for Recommendation. - Kyungwoo Song; Mingi Ji; Sungrae Park; Il-Chul Moon (AAAI, 2019)

Sequential Recommendation with Relation-Aware Kernelized Self-Attention. - Mingi Ji; Weonyoung Joo; Kyungwoo Song; Yoon-Yeong Kim; Il-Chul Moon (AAAI, 2020)

Hierarchically Clustered Representation Learning. - Su-Jin Shin; Kyungwoo Song; Il-Chul Moon (AAAI, 2020)

Bivariate Beta-LSTM. - Kyungwoo Song; JoonHo Jang; Seungjae Shin; Il-Chul Moon (AAAI, 2020)

Deep Generative Positive-Unlabeled Learning under Selection Bias. - Byeonghu Na; Hyemi Kim; Kyungwoo Song; Weonyoung Joo; Yoon-Yeong Kim; Il-Chul Moon (CIKM, 2020)

Neutralizing Gender Bias in Word Embedding with Latent Disentanglement and Counterfactual Generation. - Seungjae Shin; Kyungwoo Song; JoonHo Jang; Hyemi Kim; Weonyoung Joo; Il-Chul Moon (EMNLP (Findings), 2020)

Context Aware Sequence Modeling. - Kyungwoo Song (IJCAI, 2020)

Approximate Inference for Spectral Mixture Kernel. - Yohan Jung; Kyungwoo Song; Jinkyoo Park (CoRR, 2020)

Sequential Likelihood-Free Inference with Implicit Surrogate Proposal. - Dongjun Kim; Kyungwoo Song; Yoon-Yeong Kim; Yongjin Shin; Il-Chul Moon (CoRR, 2020)

LADA: Look-Ahead Data Acquisition via Augmentation for Active Learning. - Yoon-Yeong Kim; Kyungwoo Song; JoonHo Jang; Il-Chul Moon (CoRR, 2020)

Counterfactual Fairness with Disentangled Causal Effect Variational Autoencoder. - Hyemi Kim; Seungjae Shin; JoonHo Jang; Kyungwoo Song; Weonyoung Joo; Wanmo Kang; Il-Chul Moon (AAAI, 2021)

Implicit Kernel Attention. - Kyungwoo Song; Yohan Jung; Dongjun Kim; Il-Chul Moon (AAAI, 2021)

LADA: Look-Ahead Data Acquisition via Augmentation for Deep Active Learning. - Yoon-Yeong Kim; Kyungwoo Song; JoonHo Jang; Il-Chul Moon (NeurIPS, 2021)

Posterior-Aided Regularization for Likelihood-Free Inference. - Dongjun Kim; Kyungwoo Song; Seungjae Shin; Wanmo Kang; Il-Chul Moon (CoRR, 2021)

Score Matching Model for Unbounded Data Score. - Dongjun Kim; Seungjae Shin; Kyungwoo Song; Wanmo Kang; Il-Chul Moon (CoRR, 2021)

From Noisy Prediction to True Label: Noisy Prediction Calibration via Generative Model. - HeeSun Bae; Seungjae Shin; Byeonghu Na; JoonHo Jang; Kyungwoo Song; Il-Chul Moon (ICML, 2022)

Efficient Approximate Inference for Stationary Kernel on Frequency Domain. - Yohan Jung; Kyungwoo Song; Jinkyoo Park (ICML, 2022)

Soft Truncation: A Universal Training Technique of Score-based Diffusion Model for High Precision Score Estimation. - Dongjun Kim; Seungjae Shin; Kyungwoo Song; Wanmo Kang; Il-Chul Moon (ICML, 2022)

Learning Fair Representation via Distributional Contrastive Disentanglement. - Changdae Oh; Heeji Won; Junhyuk So; Taero Kim; Yewon Kim; Hosik Choi; Kyungwoo Song (KDD, 2022)

Unknown-Aware Domain Adversarial Learning for Open-Set Domain Adaptation. - JoonHo Jang; Byeonghu Na; DongHyeok Shin; Mingi Ji; Kyungwoo Song; Il-Chul Moon (NeurIPS, 2022)

Multi-Modal Mixup for Robust Fine-tuning. - Junhyuk So; Changdae Oh; Minchul Shin; Kyungwoo Song (CoRR, 2022)

Sharpness-aware Minimization for Worst Case Optimization. - Taero Kim; Sungjun Lim 002; Kyungwoo Song (CoRR, 2022)

BlackVIP: Black-Box Visual Prompting for Robust Transfer Learning. - Changdae Oh; Hyeji Hwang; Hee Young Lee; YongTaek Lim; Geunyoung Jung; Jiyoung Jung; Hosik Choi; Kyungwoo Song (CVPR, 2023)

Causally Disentangled Generative Variational AutoEncoder. - Seunghwan An; Kyungwoo Song; Jong-June Jeon (ECAI, 2023)

SAAL: Sharpness-Aware Active Learning. - Yoon-Yeong Kim; Youngjae Cho; JoonHo Jang; Byeonghu Na; Yeongmin Kim; Kyungwoo Song; Wanmo Kang; Il-Chul Moon (ICML, 2023)

Geodesic Multi-Modal Mixup for Robust Fine-Tuning. - Changdae Oh; Junhyuk So; Hoyoon Byun; YongTaek Lim; Minchul Shin; Jong-June Jeon; Kyungwoo Song (NeurIPS, 2023)

Robust Contrastive Learning With Dynamic Mixed Margin. - Junhyuk So; YongTaek Lim; Yewon Kim; Changdae Oh; Kyungwoo Song (IEEE Access, 2023)

RPLKG: Robust Prompt Learning with Knowledge Graph. - Yewon Kim; YongTaek Lim; Dokyung Yoon; Kyungwoo Song (CoRR, 2023)

Leveraging Skill-to-Skill Supervision for Knowledge Tracing. - Hyeondey Kim; Jinwoo Nam; Minjae Lee; Yun Jegal; Kyungwoo Song (CoRR, 2023)

Towards Calibrated Robust Fine-Tuning of Vision-Language Models. - Changdae Oh; Mijoo Kim; Hyesu Lim; Junhyeok Park; Euiseog Jeong; Zhi-Qi Cheng; Kyungwoo Song (CoRR, 2023)

Sequential Likelihood-Free Inference with Neural Proposal. - Dongjun Kim; Kyungwoo Song; Yoon-Yeong Kim; Yongjin Shin; Wanmo Kang; Il-Chul Moon; Weonyoung Joo (Pattern Recognit. Lett., 2023)

Pre-trained Vision and Language Transformers are Few-Shot Incremental Learners. - Keon-Hee Park; Kyungwoo Song; Gyeong-Moon Park (CVPR, 2024)

Perturb-and-Compare Approach for Detecting Out-of-Distribution Samples in Constrained Access Environments. - Heeyoung Lee; Hoyoon Byun; Changdae Oh; JinYeong Bak; Kyungwoo Song (ECAI, 2024)

Online Continuous Generalized Category Discovery. - Keon-Hee Park; Hakyung Lee; Kyungwoo Song; Gyeong-Moon Park (ECCV (81), 2024)

CED: Comparing Embedding Differences for Detecting Out-of-Distribution and Hallucinated Text. - Hakyung Lee; Keon-Hee Park; Hoyoon Byun; Jeyoon Yeom; Jihee Kim; Gyeong-Moon Park; Kyungwoo Song (EMNLP (Findings), 2024)

Towards Calibrated Robust Fine-Tuning of Vision-Language Models. - Changdae Oh; Hyesu Lim; Mijoo Kim; Dongyoon Han; Sangdoo Yun; Jaegul Choo; Alexander Hauptmann 001; Zhi-Qi Cheng; Kyungwoo Song (NeurIPS, 2024)

GloGen: PPG prompts for few-shot transfer learning in blood pressure estimation. - Taero Kim; Hyeonjeong Lee; Minseong Kim; Kwang-Yong Kim; Kyu Hyung Kim; Kyungwoo Song (Comput. Biol. Medicine, 2024)

Mitigating the Linguistic Gap with Phonemic Representations for Robust Multilingual Language Understanding. - Haeji Jung; Changdae Oh; Jooeon Kang; Jimin Sohn; Kyungwoo Song; Jinkyu Kim; David R. Mortensen (CoRR, 2024)

Flat Posterior Does Matter For Bayesian Transfer Learning. - Sungjun Lim 002; Jeyoon Yeom; Sooyon Kim; Hoyoon Byun; Jinho Kang; Yohan Jung; Jiyoung Jung; Kyungwoo Song (CoRR, 2024)

Robust Adaptation of Foundation Models with Black-Box Visual Prompting. - Changdae Oh; Gyeongdeok Seo; Geunyoung Jung; Zhi-Qi Cheng; Hosik Choi; Jiyoung Jung; Kyungwoo Song (CoRR, 2024)

Benchmarking Foundation Models on Exceptional Cases: Dataset Creation and Validation. - Suho Kang; Jungyang Park; Joonseo Ha; SoMin Kim; JinHyeong Kim; Subeen Park; Kyungwoo Song (CoRR, 2024)

Language model-guided student performance prediction with multimodal auxiliary information. - Changdae Oh; Minhoi Park; Sungjun Lim 002; Kyungwoo Song (Expert Syst. Appl., 2024)

Bibimbap : Pre-trained models ensemble for Domain Generalization. - Jinho Kang; Taero Kim; Yewon Kim; Changdae Oh; Jiyoung Jung; Rakwoo Chang; Kyungwoo Song (Pattern Recognit., 2024)

Structural and positional ensembled encoding for Graph Transformer. - Jeyoon Yeom; Taero Kim; Rakwoo Chang; Kyungwoo Song (Pattern Recognit. Lett., 2024)

Dirichlet stochastic weights averaging for graph neural networks. - Minhoi Park; Rakwoo Chang; Kyungwoo Song (Appl. Intell., 2024)

Tc-llama 2: fine-tuning LLM for technology and commercialization applications. - Jeyoon Yeom; Hakyung Lee; Hoyoon Byun; Yewon Kim; Jeongeun Byun; Yunjeong Choi; Sungjin Kim; Kyungwoo Song (J. Big Data, 2024)

Uncertainty-Aware Contrastive Decoding. - Hakyung Lee; Subeen Park; Joowang Kim; Sungjun Lim 002; Kyungwoo Song (ACL (Findings), 2025)

IMC: A Benchmark for Invariant Learning under Multiple Causes. - Taero Kim; Seonggyun Lee; Joonseong Kang; Youngjun Choi; Wonsang Yun; Nicole Hee-Yeon Kim; Ziyu Chen; Lexing Xie; Kyungwoo Song (CVPR Workshops, 2025)

Sufficient Invariant Learning for Distribution Shift. - Taero Kim; Subeen Park; Sungjun Lim 002; Yonghan Jung; Krikamol Muandet; Kyungwoo Song (CVPR, 2025)

Brain-inspired Lp-Convolution benefits large kernels and aligns better with visual cortex. - Jea Kwon; Sungjun Lim 002; Kyungwoo Song; C. Justin Lee (ICLR, 2025)

DaWin: Training-free Dynamic Weight Interpolation for Robust Adaptation. - Changdae Oh; Yixuan Li 001; Kyungwoo Song; Sangdoo Yun; Dongyoon Han (ICLR, 2025)

LBC: Language-Based-Classifier for Out-Of-Variable Generalization. - Kangjun Noh; Baekryun Seong; Hoyoon Byun; Youngjun Choi 001; Sungjin Song; Kyungwoo Song (NAACL (Long Papers), 2025)

Flat Posterior Does Matter For Bayesian Model Averaging. - Sungjun Lim 002; Jeyoon Yeom; Sooyon Kim; Hoyoon Byun; Jinho Kang; Yohan Jung; Jiyoung Jung; Kyungwoo Song (UAI, 2025)

Enhancing Visual Classification Using Comparative Descriptors. - Hankyeol Lee; Gawon Seo; Wonseok Choi 014; Geunyoung Jung; Kyungwoo Song; Jiyoung Jung (WACV, 2025)

Robust optimization for PPG-based blood pressure estimation. - Sungjun Lim 002; Taero Kim; Hyeonjeong Lee; Yewon Kim; Minhoi Park; Kwang-Yong Kim; Minseong Kim; Kyu Hyung Kim; Jiyoung Jung; Kyungwoo Song (Biomed. Signal Process. Control., 2025)

GFML: Gravity function for metric learning. - Hoyoon Byun; Sungjun Lim 002; Kyungwoo Song (Eng. Appl. Artif. Intell., 2025)

COVID-19 prediction with doubly multi-task Gaussian Process. - Sooyon Kim; Yongtaek Lim; Sungjun Lim 002; Gyeongdeok Seo; Jihee Kim; Hojun Park; Jaehun Jung; Kyungwoo Song (J. Biomed. Informatics, 2025)

Multi-query frequency prompting for physiological signal domain adaptation. - Jinho Kang; Hoyoon Byun; Taero Kim; Jiyoung Jung; Kyungwoo Song (Knowl. Based Syst., 2025)

Fog-free training for foggy scene understanding. - Minyoung Lee; Kyungwoo Song; Junsuk Choe (Pattern Recognit. Lett., 2025)

TC-BERT: large-scale language model for Korean technology commercialization documents. - Taero Kim; Changdae Oh; Hyeji Hwang; Eunkyeong Lee; Yewon Kim; Yunjeong Choi; Sungjin Kim; Hosik Choi; Kyungwoo Song (J. Supercomput., 2025)

Correction To: Dirichlet stochastic weights averaging for graph neural networks. - Minhoi Park; Rakwoo Chang; Kyungwoo Song (Appl. Intell., 2025)

Adaptive Task Vectors for Large Language Models. - Joonseong Kang; Soojeong Lee; Subeen Park; Sumin Park; Taero Kim; Jihee Kim; Ryunyi Lee; Kyungwoo Song (CoRR, 2025)

Multi-purpose technology commercialization recommender system with large-scale Korean language model. - Kangjun Noh; Hyeji Hwang; YongTaek Lim; Changdae Oh; Seungyeon Kim; Eunkyeong Lee; Yunjeong Choi; Sungjin Kim; Hosik Choi; Kyungwoo Song (J. Supercomput., 2025)

Uncertainty-driven Embedding Convolution. - Sungjun Lim 002; Kangjun Noh; Youngjun Choi; Heeyoung Lee; Kyungwoo Song (CoRR, 2025)

Graph Perceiver IO: A general architecture for graph-structured data. - Seyun Bae; Hoyoon Byun; Changdae Oh; Yoon-Sik Cho; Kyungwoo Song (Pattern Recognit., 2026)